Screening tests can help find cancer at an early stage, before symptoms appear. When abnormal tissue or cancer is found early, it may be easier to treat or cure. By the time symptoms appear, the cancer may have grown and spread. This can make the cancer harder to treat or cure.
It is important to remember that when your doctor suggests a screening test, it does not always mean he or she thinks you have cancer. Screening tests are done when you have no cancer symptoms.
Screening tests include the following:
Not all screening tests are helpful and most have risks. It is important to know the risks of the test and whether it has been proven to decrease the chance of dying from cancer.
Screening test results may appear to be abnormal even though there is no cancer. A false-positive test result (one that shows there is cancer when there really isn't) can cause anxiety and is usually followed by more tests and procedures, which also have risks.
Screening test results may appear to be normal even though there is cancer. A person who receives a false-negative test result (one that shows there is no cancer when there really is) may delay seeking medical care even if there are symptoms.
Some cancers never cause symptoms or become life-threatening, but if found by a screening test, the cancer may be treated. There is no way to know if treating the cancer would help the person live longer than if no treatment were given. Also, treatments for cancer have side effects.
For some cancers, finding and treating the cancer early does not improve the chance of a cure or help the person live longer.
Scientists study screening tests to find those with the fewest risks and most benefits. The PDQ cancer screening summaries are based on the results of these studies and other scientific information about cancer risk and screening tests. The summaries are written to give readers the most current information about standard screening tests and tests that are being studied in clinical trials.
It can be hard to make decisions about screening tests. Before having any screening test, you may want to discuss the test with your doctor.
A screening test that works the way it should and is helpful does the following:
Screening tests usually do not diagnose cancer. If a screening test result is abnormal, more tests may be done to check for cancer. For example, a screening mammogram may find a lump in the breast. A lump may be cancer or something else. More tests need to be done to find out if the lump is cancer. These are called diagnostic tests. Diagnostic tests may include a biopsy, in which cells or tissues are removed so a pathologist can check them under a microscope for signs of cancer.
Anything that increases the chance of cancer is called a cancer risk factor. Having a risk factor does not mean that you will get cancer; not having risk factors doesn’t mean that you will not get cancer.
Some screening tests are used only for people who have known risk factors for certain types of cancer. People known to have a higher risk of cancer than others include those who:
People who have a high risk of cancer may need to be screened more often or at an earlier age than other people.
Scientists are trying to better understand who is likely to get certain types of cancer. They study the things we do and the things around us to see if they cause cancer. This information helps doctors figure out who should be screened for cancer, which screening tests should be used, and how often the tests should be done.
Since 1973, the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute has been collecting information on people with cancer from different parts of the United States. Information from SEER, research studies, and other sources is used to study who is at risk.
Cancer risk is measured in different ways. The findings from surveys and studies about cancer risk are studied and the results are explained in different ways. Some of the ways risk is explained include absolute risk , relative risk , and odds ratios .
This is the risk a person has of developing a disease, in a given population (for example, the entire U.S. population) over a certain period of time. Researchers estimate the absolute risk by studying a large number of people that are part of a certain population (for example, women in a given age group). Researchers count the number of people in the group who get a certain disease over a certain period of time. For example, a group of 100,000 women between the ages of 20 and 29 are observed for one year, and 4 of them get breast cancer during that time. This means that the one-year absolute risk of breast cancer for a woman in this age group is 4 in 100,000, or 4 chances in 100,000.
This is often used in research studies to find out whether a trait or a factor can be linked to the risk of a disease. Researchers compare two groups of people who are a lot alike. However, the people in one of the groups must have the trait or factor being studied (they have been “exposed”). The people in the other group do not have it (they have not been exposed). To figure out relative risk, the percentage of people in the exposed group who have the disease is divided by the percentage of people in the unexposed group who have the disease.
Relative risks can be:
Relative risks are also called risk ratios.
In some types of studies, researchers don’t have enough information to figure out relative risks. They use something called an odds ratio instead. An odds ratio can be an estimate of relative risk.
One type of study that uses an odds ratio instead of relative risk is called a case-control study. In a case-control study, two groups of people are compared. However, the individuals in each group are chosen based on whether or not they have a certain disease. Researchers look at the odds that the people in each group were exposed to something (a trait or factor) that might have caused the disease. Odds describes the number of times the trait or factor was present or happened, divided by the number of times it wasn’t present or didn’t happen. To get an odds ratio, the odds for one group are divided by the odds for the other group.
Odds ratios can be:
Looking at traits and exposures in people with and without cancer can help find possible risk factors. Knowing who is at an increased risk for certain types of cancer can help doctors decide when and how often they should be screened.
For many cancers, the chance of recovery depends on the stage (the amount or spread of cancer in the body) of the cancer when it was diagnosed. Cancers that are diagnosed at earlier stages are often easier to treat or cure.
Studies of cancer screening compare the death rate of people screened for a certain cancer with the death rate from that cancer in people who were not screened. Some screening tests have been shown to be helpful both in finding cancers early and in decreasing the chance of dying from those cancers. Other tests are used because they have been shown to find a certain type of cancer in some people before symptoms appear, but they have not been proven to decrease the risk of dying from that cancer. If a cancer is fast-growing and spreads quickly, finding it early may not help the person survive the cancer.
When collecting information on how long cancer patients live, some studies define survival as living 5 years after the diagnosis. This is often used to measure how well cancer treatments work. However, to see if screening tests are useful, studies usually look at whether deaths from the cancer decrease in people who were screened. Over time, signs that a cancer screening test is working include:
The number of deaths from cancer is lower today than it was in the past. It is not always clear if this is because screening tests found the cancers earlier or because cancer treatments have gotten better, or both. The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute collects and reports information on survival times of people with cancer in the United States. This information is studied to see if finding cancer early affects how long these people live.
These factors include lead-time bias and overdiagnosis.
Survival time for cancer patients is usually measured from the day the cancer is diagnosed until the day they die. Patients are often diagnosed after they have signs and symptoms of cancer. If a screening test leads to a diagnosis before a patient has any symptoms, the patient’s survival time is increased because the date of diagnosis is earlier. This increase in survival time makes it seem as though screened patients are living longer when that may not be happening. This is called lead-time bias. It could be that the only reason the survival time appears to be longer is that the date of diagnosis is earlier for the screened patients. But the screened patients may die at the same time they would have without the screening test.
Sometimes, screening tests find cancers that don't matter because they would have gone away on their own or never caused any symptoms. These cancers would never have been found if not for the screening test. Finding these cancers is called overdiagnosis. Overdiagnosis can make it seem like more people are surviving cancer longer, but in reality, these are people who would not have died from cancer anyway.
Evidence about how safe, accurate, and useful cancer screening tests are comes from clinical trials (research studies with people) and other kinds of research studies. When enough evidence has been collected to show that a screening test is safe, accurate, and useful, it becomes a standard test. Examples of cancer screening tests that were once under study but are now standard tests include:
Cancer screening trials study new ways of finding cancer in people before they have symptoms. Screening trials also study screening tests that may find cancer earlier or are more accurate than existing tests, or that may be easier, safer, or cheaper to use. Screening trials are designed to find the possible benefits and possible harms of cancer screening tests. Different clinical trial designs are used to study cancer screening tests.
The strongest evidence about screening comes from research done in clinical trials. However, clinical trials cannot always be used to study questions about screening. Findings from other types of studies can give useful information about how safe, useful, and accurate cancer screening tests are.
Randomized controlled trials give the highest level of evidence about how safe, accurate, and useful cancer screening tests are. In these trials, volunteers are assigned randomly (by chance) to one of two or more groups. The people in one group (the control group) may be given a standard screening test (if one exists) or no screening test. The people in the other group(s) are given the new screening test(s). Test results for the groups are then compared to see if the new screening test works better than the standard test, and to see if there are any harmful side effects.
Using chance to assign people to groups means that the groups will probably be very much alike and that the trial results won't be affected by human choices or something else.
In nonrandomized clinical trials, volunteers are not assigned randomly (by chance) to different groups. They choose which group they want to be in or the study leaders assign them. Evidence from this type of research is not as strong as evidence from randomized controlled trials.
A cohort study follows a large number of people over time. The people are divided into groups, called cohorts, based on whether or not they have had a certain treatment or been exposed to certain things. In cohort studies, the information is collected and studied after certain outcomes (such as cancer or death) have occurred. For example, a cohort study might follow a group of women who have regular Pap tests, and divide them into those who test positive for the human papillomavirus (HPV) and those who test negative for HPV. The cohort study would show how the cervical cancer rates are different for the two groups over time.
Case-control studies are like cohort studies but are done in a shorter time. They do not include many years of follow-up. Instead of looking forward in time, they look backward. In case-control studies, information is collected from cases (people who already have a certain disease) and compared with information collected from controls (people who do not have the disease). For example, a group of patients with melanoma and a group without melanoma might be asked about how they check their skin for abnormal growths and how often they check it. Based on the different answers from the two groups, the study may show that checking your skin is a useful screening test to decrease the number of melanoma cases and deaths from melanoma.
Evidence from case-control studies is not as strong as evidence from clinical trials or cohort studies.
Ecologic studies report information collected on entire groups of people, such as people in one city or county. Information is reported about the whole group, not about any single person in the group. These studies may give some evidence about whether a screening test is useful.
The evidence from ecologic studies is not as strong as evidence from clinical trials or other types of research studies.
Expert opinions can be based on the experiences of doctors or reports of expert committees or panels. Expert opinions do not give strong evidence about the usefulness of screening tests.